PERF: setting values via df.loc / df.iloc with pyarrow-backed columns

asv_bench/benchmarks/array.py

@@ -90,6 +90,9 @@ def time_setitem_list(self, multiple_chunks):
     def time_setitem_slice(self, multiple_chunks):
         self.array[::10] = "foo"
 
+    def time_setitem_null_slice(self, multiple_chunks):
+        self.array[:] = "foo"
+
     def time_tolist(self, multiple_chunks):
         self.array.tolist()
 

doc/source/whatsnew/v2.0.0.rst

@@ -748,6 +748,7 @@ Performance improvements
 - Reduce memory usage of :meth:`DataFrame.to_pickle`/:meth:`Series.to_pickle` when using BZ2 or LZMA (:issue:`49068`)
 - Performance improvement for :class:`~arrays.StringArray` constructor passing a numpy array with type ``np.str_`` (:issue:`49109`)
 - Performance improvement in :meth:`~arrays.ArrowExtensionArray.factorize` (:issue:`49177`)
+- Performance improvement in :meth:`~arrays.ArrowExtensionArray.__setitem__` when key is a null slice (:issue:`50248`)
 - Performance improvement in :meth:`~arrays.ArrowExtensionArray.to_numpy` (:issue:`49973`)
 - Performance improvement in :meth:`DataFrame.join` when joining on a subset of a :class:`MultiIndex` (:issue:`48611`)
 - Performance improvement for :meth:`MultiIndex.intersection` (:issue:`48604`)

pandas/core/arrays/arrow/array.py

@@ -40,6 +40,7 @@
 
 from pandas.core.arraylike import OpsMixin
 from pandas.core.arrays.base import ExtensionArray
+import pandas.core.common as com
 from pandas.core.indexers import (
     check_array_indexer,
     unpack_tuple_and_ellipses,
@@ -931,9 +932,31 @@ def __setitem__(self, key: int | slice | np.ndarray, value: Any) -> None:
         None
         """
         key = check_array_indexer(self, key)
-        indices = self._indexing_key_to_indices(key)
         value = self._maybe_convert_setitem_value(value)
 
+        # fast path (GH50248)
+        if com.is_null_slice(key):
+            if is_scalar(value):
+                fill_value = pa.scalar(value, type=self._data.type, from_pandas=True)
+                try:
+                    self._data = pc.if_else(True, fill_value, self._data)
+                    return
+                except pa.ArrowNotImplementedError:
+                    # ArrowNotImplementedError: Function 'if_else' has no kernel
+                    #   matching input types (bool, duration[ns], duration[ns])
+                    # TODO: remove try/except wrapper if/when pyarrow implements
+                    #   a kernel for duration types.
+                    pass
+            elif len(value) == len(self):
+                if isinstance(value, type(self)) and value.dtype == self.dtype:
+                    self._data = value._data
+                else:
+                    arr = pa.array(value, type=self._data.type, from_pandas=True)
+                    self._data = pa.chunked_array([arr])
+                return
+
+        indices = self._indexing_key_to_indices(key)
+
         argsort = np.argsort(indices)
         indices = indices[argsort]
 

pandas/tests/extension/test_arrow.py

@@ -1438,3 +1438,48 @@ def test_to_numpy_with_defaults(data):
         expected[pd.isna(data)] = pd.NA
 
     tm.assert_numpy_array_equal(result, expected)
+
+
+def test_setitem_null_slice(data):
+    # GH50248
+    orig = data.copy()
+
+    result = orig.copy()
+    result[:] = data[0]
+    expected = ArrowExtensionArray(
+        pa.array([data[0]] * len(data), type=data._data.type)
+    )
+    tm.assert_extension_array_equal(result, expected)
+
+    result = orig.copy()
+    result[:] = data[::-1]
+    expected = data[::-1]
+    tm.assert_extension_array_equal(result, expected)
+
+    result = orig.copy()
+    result[:] = data.tolist()
+    expected = data
+    tm.assert_extension_array_equal(result, expected)
+
+
+def test_setitem_invalid_dtype(data):
+    # GH50248
+    pa_type = data._data.type
+    if pa.types.is_string(pa_type) or pa.types.is_binary(pa_type):
+        fill_value = 123
+        err = pa.ArrowTypeError
+        msg = "Expected bytes"
+    elif (
+        pa.types.is_integer(pa_type)
+        or pa.types.is_floating(pa_type)
+        or pa.types.is_boolean(pa_type)
+    ):
+        fill_value = "foo"
+        err = pa.ArrowInvalid
+        msg = "Could not convert"
+    else:
+        fill_value = "foo"
+        err = pa.ArrowTypeError
+        msg = "cannot be converted"
+    with pytest.raises(err, match=msg):
+        data[:] = fill_value